Method and apparatus for network planning

ABSTRACT

A system and method for wireless network planning utilizing raster data, stored and manipulated in raster data planes ( 204–212 ) and vector data ( 522 ) stored and manipulated in vector data planes ( 528–532 ). The invention increases the accuracy of network planning by simultaneously utilizing vector data planes ( 528–532 ) and raster data planes ( 204–212 ) to perform computations using vector features contained within map pixels ( 604 ). The disclosed method makes it possible to perform accurate computations such as propagation loss to vector points ( 602 ) contained within map pixels ( 604 ). Accuracy is further increased because other characteristics such as received power, elevation, and best server can be computed to the vector features rather than processing them with traditional raster resolutions.

FIELD OF THE INVENTION

The present invention generally relates to network planning and moreparticularly to handling vector data for wireless network planning.

BACKGROUND OF THE INVENTION

Wireless communications systems are used to satisfy a variety of mobilevoice and data communication needs. Currently, there is demand foradditional wireless capabilities so that customers can expand their useof wireless communication devices. This demand is forcing wirelessservice providers to expand their networks at a rapid rate. The mobilityof wireless communication users complicates the deployment of additionalnetwork infrastructure such as base stations.

Wireless networks are complex because the infrastructure is often spreadover large geographic regions, wireless signals are attenuated as afunction of distance, and wireless traffic is not evenly distributedover the served region (e.g. wireless traffic is often clustered intodefined areas such as along roadways). Network engineers model wirelessnetworks before deploying system hardware to ensure complete signalcoverage and adequate channel capacity. Currently, computer basedplanning tools are used to perform the complex computations necessaryfor modelling a wireless network. These models use digitized mapdatabases, geographic coordinates, terrain data, and feature data in anattempt to account for important design constraints. However, the use ofdigitized map databases undesirably limits the accuracy of computerizednetwork planning.

Since digital maps represent sampled data, there is a spacing betweenadjacent sample points. The area between each sample point is referredto as a map pixel. The size of each map pixel varies based on the samplespacing used. For example, the area of each map pixel is approximately90 meters north-south by 70 meters east-west for a 3 arc second USGSmap, which is normally used for wireless network planning. Currentplanning tools use the map pixel as the smallest unit of reference;therefore, features smaller than a map pixel in one dimension are notaccurately interpreted. Several types of features used in wirelessnetwork planning are smaller than a map pixel in one dimension.Accurately modelling the distance to these features is desirable.Features smaller than a map pixel in one dimension are normally referredto as vectors, with roads and county boundaries being among the mostcommon vector types encountered in wireless network planning.

FIG. 1 illustrates a road 104 traversing map pixels 102. The shadedpixels indicate how the road is perceived after it is rasterized. It canbe seen in FIG. 1 that the road value is attributed to the entire pixeleven though the road only touches a portion of the pixel. Attributingthe road attribute to the entire pixel introduces errors. The errorsintroduced by using map pixels as the smallest measurement unit areespecially problematic when performing propagation loss calculations topoints located along a vector. For example, if a car is on a narrow roadrunning through the middle of a map pixel, a propagation calculation tothe road can only be computed to an edge of the map pixel containing theroad. In addition, other information such as elevation andland-use-land-cover (LULC) are averaged across the entire map pixel,further introducing errors. Thus, the road 104 is not modeled accuratelyenough to achieve optimum results.

Therefore, a need exists for more accurately computing distances topoints along vectors when performing network planning. Furthermore,computing the distance to vector features should not overly burden datastorage systems by generating excessive data points.

SUMMARY OF THE INVENTION

It is an advantage of the present invention that a system and method areprovided for incorporating the accuracy of vector data into networkplanning without incurring the penalties realized when all pertinentdata is treated with the same granularity. The disclosed invention makesit possible to perform accurate distance dependent propagation losscalculations to vector features located within map pixels. Furthermore,the present invention surpasses current art methods when modellingtransient roadway events, such as traffic jams.

The above and other advantages of the present invention are carried outin a network planning system where many input and output variables arerequired and computed. Variables are stored in data planes which areindexed by geographical location. The use of data planes makes itpossible to store non-vector data and vector data with separategranularities while using a single geographical coordinate system. Someexamples of non-vector data which are also common to vectors are baseelevation and terrain. Data common to vectors and non-vectors is onlystored in a single data plane. In contrast, variables unique to eachdata type are stored in the respective data planes. An example of avariable unique to vector data planes is width. Keeping unique variablesin the respective data plane ensures that other processes, such asdisplay system processing and computations, can determine when aspecific variable should be accounted for.

BRIEF DESCRIPTION OF THE DRAWING

A more complete understanding of the present invention may be derived byreferring to the detailed description and the claims when considered inconnection with the Figures, wherein like reference numbers refer tosimilar items throughout the Figures, and:

FIG. 1—is an illustration showing a prior art method of rasterizing aroad;

FIG. 2—is an illustration of data planes as used by the presentinvention;

FIG. 3—illustrates a method for identifying map pixels using a uniqueidentifier;

FIG. 4—is an illustration of a comprehensive display created using dataplanes;

FIG. 5—is an illustration showing generation of vectors on data planes;

FIG. 6—is an illustration showing superposition of vector points on agrid of map pixels;

FIG. 7—illustrates a flow diagram of steps used in wireless networkplanning;

FIG. 8—is an illustration showing radial signal paths for map pixeldisplay;

FIGS. 9A and 9B—illustrate a pixel representation of a propagation pathloss calculation;

FIG. 10—illustrates a flow diagram of a method for computing propagationloss;

FIG. 11—is an illustration of a representative apparatus for performinginvention;

FIG. 12—provides a map showing road orientations;

FIGS. 13A and 13B—illustrate the use of vector data; and

FIG. 14—is an illustration showing propagation losses for various roadorientations.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

A typical wireless network consists of at least one base station (BSS),or cell site, associated with a specific geographic location within theservice area. Cell sites can be further divided into macro cell or microcell sites depending on the antenna height and area served. The presentinvention can be used for planning macro and micro cells; however,descriptions of the invention and preferred embodiments will bediscussed in the context of the more general macro cells. Often a BSScontains more than one antenna in order to serve a larger area. Whenmore than one antenna is used, each antenna serves a particular area,known as a sector, around the BSS location. In situations where signalsfrom more than one antenna reach a particular location within the BSSservice area, the antenna producing the stronger signal at the measuredlocation is referred to as the best server.

Maps

Line-of-sight (LOS) from BSS to mobile receiver is required for signalreception; therefore, network planners must take into account terrainfeatures, land-use-land-cover (LULC), population density, foliage, etc.Since BSS locations, mobile receiver locations, elevations, and land usefeatures can be uniquely identified by geographic location, representingthese features of interest on geographic maps is convenient. Rasterizedmaps are used to display feature data on a general purpose computersystem using the disclosed method. Any type of rasterized map databasecan be used; however, for cellular network planning most networkplanners use the USGS 3 arc second database. The 3 arc second databaseprovides a reasonable compromise between database size and geographiclocation resolution. Rasterized maps consist of sampled data with thearea between each sample point referred to as a map pixel. A map pixelis the smallest unit of resolution for a given set of digitized mapdata. As previously noted, each map pixel is approximately 90 m N-S×70 mE-W for a 3 arc-second raster map.

When performing computerized wireless network planning, it is helpfulfor planners to have a comprehensive display capability so that variousinformation types can be displayed simultaneously. For example, acomprehensive display allowing the network planner to view BSSlocations, terrain features, population density, and road locations atthe same time allows the planner to quickly comprehend the results of agiven network configuration. The present invention producescomprehensive displays by creating multi-dimensional maps. Themulti-dimensional maps are produced by manipulating multiple data types(variables) relative to a reference to produce a meaningful display.

Raster Data Planes

FIG. 2 illustrates raster data planes, hereinafter referred to as dataplanes, as used by the present invention. Data planes are used toproduce multi-dimensional maps. Typically, data planes are comprised ofregularly arranged points corresponding to a rectangular grid. Thesedata planes are assigned such that each variable is represented by asingle plane. Some data planes may contain input variables such aselevation 204, land cover 206, and land use 208 which are required tocompute a radio plan. Others data planes contain output variables suchas best server 210, and received power 212. Additionally, a user cancreate data planes containing other user-defined variables as needed tofacilitate a given wireless planning task. To minimize storagerequirements, variables common to more than one data plane are onlystored in one of the data planes. For example, if the elevation variableis used by both a road data plane and a terrain data plane, it will onlybe stored in one data plane and made accessible to other data planesrequiring the information.

FIG. 3 illustrates a technique used in the present invention foridentifying map pixels using unique points. Unique points are used toidentify map pixels in the following discussion, however personsknowledgeable in the art will readily comprehend that other methods canbe used to identify map pixels without departing from the spirit of thedisclosed invention. FIG. 3 contains uniform map pixels 312, 314, 316,and 318. Note that the south-west corner of each map pixel has beenselected as the unique identification point. Using the southwest cornerto identify each map pixel produces the following relationships: corner302 is used to identify map pixel 312, corner 308 is used to identifymap pixel 318, and corner 304 is used to identify map pixel 314.

Exemplary Display Using Data Planes

FIG. 4 presents a representative display requiring the use of multipledata planes. A base station 400 is shown having three antennas whichform three sectors having best server areas 402, 404, and 406,respectively. The land use within the entire served area 412 is uniformexcept for water body 408. In addition, features of interest, namelyroads 410 and 414 are shown. Although multiple data planes are used torepresent the data, overall accuracy of network planning is not enhancedwithout additional processing. The mere use of data planes does notenhance accuracy because all data such as LULC, population density, andwireless traffic density are represented as an average value for anentire map pixel. For example, a single point located on highway medianstrip would have the same population density value as the inhabitedareas adjacent to the highway if resolution is limited to the area of amap pixel.

The present invention makes it possible to accurately compute thedistance to, and properties of, intra-pixel features. The foregoingdiscussions will detail correct processing of vector data; however, itwill be apparent to those skilled in the art that the techniquesdisclosed herein can be used on other intra-pixel features withoutdeparting from the spirit of the invention.

Vectors Generally

FIG. 5 illustrates the definition of a feature as a set of pointsconnected by straight lines. A vector 516 was created by connectingpoints 519, 520, 522 and 524, respectively. Data storage requirementsassociated with vectors are optimized by storing the minimum number ofpoints required to adequately represent the particular vector. Forexample, if a vector feature makes a tight turn, the points used todenote it will be close together 518. For a vector feature that runsstraight, the points can be far apart 516.

To accommodate vector features of varying width, a separate inputvariable is used to specify the width of the vector feature. In general,the database used to store vector features is smaller in size than themap pixel database because most map pixels will not contain roads, landboundaries, or other features which are represented by vectors. However,if vector features are complex, the vector database can be made largerto accommodate more detail than is required for storing map pixels.

Vectors and Data Planes

The variables associated with vectors are organized as a set of webbeddata planes, as shown in FIG. 5, one plane per variable. Three dataplanes are shown in FIG. 5, namely coordinate 528, relative elevation530 and best server 532. When the same coordinate system is used forboth the map pixel data planes and the vector data planes, vectors canbe visually and logically superimposed for both display to the networkplanner and for computer calculations. When practicing the disclosedinvention, there is no requirement that the granularity of the vectorand map pixel planes be coordinated.

FIG. 6 shows a superposition of two vector points 602 and 610 on a gridof map pixels 604. There is no need to store a vector point at map pixel606 or 608 because points 602 and 610 are connected by a straight line.Any vector values needed for calculations within those map pixels can bederived by interpolation. For instance, if the vector points represent aroad that is 10 m above the surrounding terrain, the elevation of theroad in map pixel 606 will be 10 m above the terrain of that pixel.Accurately representing vector features is critical to producingrealistic wireless network plans using computerized planning systems.

Exemplary Steps for Wireless Planning

FIG. 7 shows the major steps used for wireless network planning. Here itis noted that additional steps can be added to the diagram of FIG. 7without departing from the spirit of the disclosed invention. Step 702uses input variables, including geographic data and user specifiedoperating constraints. The information inputted in step 702 is used by apropagation module (step 704) to compute the expected signal strength ateach map feature, including vector features. The propagation calculationis performed at least once for each base station in the coverage area.If vector features are not present in a particular pixel, traditionalraster processing is performed. When one or more vector features arepresent in the pixel being processed, the vector processing as disclosedherein is used. The output of the propagation module (step 704) feedsthe best server module (step 706). The best server module (step 706)selects the base station that should be serving each map pixel. In theevent that more than one base station is serving a particular map pixel,the best server module (step 706) selects the base station producing thestrongest signal at the map pixel and assigns the received signal tothat base station. The output of the propagation module (step 704) andthe best server module (step 706) are inputted to the pairwiseCarrier-to-Interference (C/I) module (step 708). The output of the C/Imodule (step 708) is inputted to the frequency assignment module in step710. The frequency assignment module (step 710) performs the assignmentof frequencies to particular channels within the network. In FIG. 7,best server module (step 706) is shown outputting data to probableneighbor module (step 712). The dashed line connecting the output ofstep 712 to step 710 is used to indicate that the respective connectioncan be eliminated if desired.

Propagation Loss Generally

An important result of wireless network planning is the determination ofexpected signal-to-noise ratios for all possible mobile receiverlocations within the service area. As previously mentioned, accuratelypredicting the distance dependent propagation loss to locations withinthe service area is essential to producing an accurate wireless plan.Many methods exist for computing the propagation loss; however, ageneralized form can be written in dB units asP _(receiver) =P _(transmit) +G _(base) −L+G _(mobile);   Eq. 1

where P_(receiver)=power at the mobile receiver

-   -   P_(transmit)=transmit power of the base station    -   G_(base)=base station antenna gain    -   L=propagation path loss, a positive quantity    -   G_(m)=mobile station antenna gain        P_(transmit), G_(base), and G_(m) are design quantities. As        such, P_(transmit), G_(base), and G_(m) can be chosen by the        network designer.

Propagation path loss, L, is computed for a particular base station tomobile receiver geometry. A general equation for the propagation pathloss at a particular receiver location can be written asL=L _(basic) +L _(obstacle) −G _(slope) −G _(water) +L _(rain);   Eq. 2

where L=total propagation path loss at a particular receiver location

-   -   L_(basic)=computed losses using a basic propagation model    -   L_(obstacle)=loss attributable to obstacles in the LOS path        between the base station and receiver    -   G_(slope)=gain attributable to terrain slope at receiver        location    -   G_(water)=gain attributable to water's surface in vicinity of        receiver    -   L_(rain)=loss attributable to rain falling in LOS path between        base station and receiver        L_(basic) has the largest impact on the final result. L_(basic)        represents the LOS distance dependent propagation loss as the        transmitted signal travels through air. Several types of models        are known and used in the art to compute L_(basic) such as the        Longley-Rice and Okumura-Hata models, and any of them can be        used with the present invention. Since L_(basic) is distance        dependent, it is important that the network designer accurately        identify the distance between the base station location and        potential mobile receiver locations for every point within the        wireless network area.

Radial Signal Paths

FIG. 8 shows multiple radial signal paths represented on a map pixelbackground 800. The disclosed method makes it possible to compute theactual distance from a BSS to any point on a vector, thus producingincreased accuracy for the distance dependent propagation calculation.Computing propagation loss begins with establishing radials from a BSSto a desired location pixel. Radials are shown in FIG. 8 as paths 804,806, 808 and 810. The radials are traced along straight lines emanatingfrom the BSS 802 to various mobile antenna locations. The map pixelbackground, or alternatively pixel map, can be thought of as a grid withthe radials approximated by a sequence of map pixels 812 and 814.

The path loss calculations are very complex and time consuming;therefore, techniques are employed to minimize computation times. Forexample, the result of each raster path loss calculation is saved as amap pixel output variable. Once the path loss for a particular map pixelhas been calculated and stored, it will not be recomputed if anotherradial passes through it. Instead the stored value will be used againfor subsequent radials passing through that pixel.

Variables Used in Propagation Modelling

After the radials are computed against the map pixel background, inputvariables and calculation parameters are used to further enhance thepath loss calculation associated with each map pixel. The variables foreach map pixel are retrieved from the appropriate data planes. Someexamples of common input variables and calculation parameters are shownin Table 1; however, other input variables and calculation parameterscan also be used.

TABLE 1 Propagation Path Loss Calculation Inputs Input/pixel CalculationParameters Terrain Elevation Model To be Used Location TransmitterHeight Land Use/Cover Mobile Antenna Height Attenuation for Land UseFrequency Average Height for Land Use Resolution Desired Height ofObstacles Window width for Effective Antenna Height Orientation of RoadPixels Window width for Average Land Use Road Orientation AngleTolerance

Exemplary Propagation Loss Geometry

FIGS. 9A and B illustrate the relationships for some of the parametersidentified in Table 1. In FIG. 9A, a base station (BSS) 902 having anantenna height 903 sits at a particular elevation. The BSS elevation iscomputed as an average of the elevation of map pixels 906 surroundingthe location of BSS 902. A mobile unit 904, having a mobile antennaheight 905 is located a radial distance 901 away from base station 902.The attenuation factor selected is based on the land use at the mobileunit's location. The land use at the mobile unit's location iscalculated using the land use average window 908 and a weightingfunction 910.

It may be helpful for the reader to visualize the radial distance 901 asa profile shown in FIG. 9B. The profile is achieved by taking a planarslice perpendicular to the earth's surface passing through both the basestation 902 and the mobile unit 904. BSS 902 is positioned at location914 having an elevation 912. The area from 914 through 915 steps up inelevation and has land cover #1. The land cover transitions to landcover #3 at map pixel 916. Mobile unit 904 is positioned at 922 at anelevation 924. Land cover #3 extends from map pixel 916 to map pixel 920where the mobile antenna 904 is positioned at distance 901. There is acomputable LOS distance 926 between the BSS 902 and the mobile antenna904.

Exemplary Method for Computing Propagation Loss

FIG. 10 presents a flow diagram showing a preferred method of computingthe propagation path loss and the corresponding received power. In step1000, the process retrieves the calculation parameters to be used suchas the maximum radius from the base station (BSS). For each basestation, the process initializes to a starting radial, step 1002. Theprocess starts with closest map pixel, step 1004. Step 1006 determinesif the map pixel is within the maximum radius, and if so, the processfurther determines if the received power for that pixel has beencomputed for this base station, step 1003. If the receive power has notbeen calculated for the pixel of interest, then the process computes thepath loss for the map pixel of interest using the selected model, step1008. Next, the received power is computed in step 1009 and the resultis stored in the output variable data plane, step 1010. If the receivepower has been computed, the process increments out along the radial instep 1012 and repeats. The process then increments the radial anadditional pixel, and returns to step 1004.

When the process reaches the limit in step 1006, it checks to ensurethat all radials required for the particular base station have beencalculated, step 1014. If not, the angle of the radial is incremented,step 1016, and the propagation path loss for the pixels in the nextradial are calculated. When calculations are completed for one basestation, the process computes the necessary values for the next basestation, step 1018. The process repeats until calculations have beenperformed for all relevant base stations within the selected coveragearea.

To account for the overlap of base station service areas, the process isfurther enhanced to account for instances where the received power fromone base station is recorded for a map pixel that can also be served bya second base station. Once the received power from the second basestation is calculated, the two possible powers are compared. The largervalue is stored as the received power from the best server, while thesecond largest is retained elsewhere in the database.

Exemplary Apparatus for Practicing Method

FIG. 11 generally illustrates a computerized wireless network planningapparatus 1100 capable of performing the required operations necessaryto practice the invention. Processor 1102 may be any type ofconventional processing device that interprets and executesinstructions. Main memory 1104 may be a random access memory (RAM) or asimilar dynamic storage device. Main memory 1104 stores information andinstructions executed by processor 1102. Main memory 1104 may also beused for storing temporary variables or other intermediate informationduring execution of instructions by processor 1102. ROM 1106 storesstatic information and instructions for processor 1102. It will beappreciated that ROM 1106 may be replaced with some other type of staticstorage device. The data storage device 1108 may include any type ofmagnetic or optical media and its corresponding interfaces andoperational hardware. Data storage device 1108 stores information andinstructions for use by processor 1102. Furthermore, main memory 1104,ROM 1106, and storage device 1108 can reside locally within the wirelessnetwork planning apparatus 1100, or they can reside remotely. If mainmemory 1104, ROM 1106 and storage device 1108 reside remotely, datanecessary for proper operation of the wireless network planningapparatus 1100 will be communicated via a coupling means such as anInternet, intranet, telephone line, or wireless communications signal.Bus 1110 includes a set of hardware lines (conductors, optical fibers,or the like) that allow for data transfer among the components of thecomputerized wireless network planning apparatus 1100.

The display device 1112 may be a cathode ray tube (CRT), LCD, or thelike, for displaying information to a user. Alternatively, the displaydevice 1112 can be omitted and any interim or final data normallydisplayed to an operator, can be sent to another output device such as aprinter or hard disk. Keyboard 1114 and cursor control 1116 allow theuser to interact with the wireless network planning apparatus 1100 whileperforming network planning. The cursor control 1116 may be, forexample, a mouse. In an alternative configuration, the keyboard 1114 andcursor control 1116 can be replaced with a microphone and voicerecognition means to enable the user to interact with the wirelessnetwork planning apparatus 1100.

Communication interface 1118 enables the wireless network planningapparatus 1100 to communicate with other devices/systems via anycommunications medium. For example, communication interface 1118 may bea modem, an Ethernet interface to a LAN, or a printer interface.Alternatively, communication interface 1118 can be any other interfacethat enables communication between the wireless network planningapparatus 1100 and other devices or systems.

Execution of the sequences of instructions contained in memory 1104causes processor 1102 to perform the method as illustrated in FIG. 10,and the methods described hereinafter. For example, processor 1102 mayexecute instructions to perform the functions of propagation loss forroads, generation of vector features, and display of interim and finalresults. It will be obvious to practitioners in the art, that hard-wiredcircuitry may be used in place of, or in combination with, softwareinstructions to implement the present invention. Thus, the presentinvention is not limited to any specific combination of hardwarecircuitry and software.

Propagation Loss for Vectors

When roads and other vectors are rasterized using prior at methods, theentire pixel containing a road is given a land use of open/road. It isknown in the art that the attenuation factor for a road is equivalent toopen space and less than that of other land cover types. When a roadparallels a radial drawn from a base station, there is a path of lowattenuation along the road. For a parallel radial, the low attenuationpath can be many pixels in length. In contrast, if the road isperpendicular to the radial, only one map pixel will have the lowerattenuation factor. In actual network planning, it is unlikely that aroad will be perfectly parallel to a radial; therefore, for thedisclosed invention parallel is defined as within a specified angle ofdeviation from the radial. Typically, a radial can deviates 10–20° fromthe angle of the road is still considered parallel to the road; however,angles outside the 10–20° range can also be used.

FIG. 12, shows a map portion in which the road is both parallel to, andperpendicular to the radial emanating from the base station 1200. A road1202 runs across FIG. 12 and passes along side base station 1200. Radial1206 emanates from base station 1200 and runs toward the upper rightcorner of FIG. 12. Radial 1206 runs parallel to the road segment 1212,and it runs perpendicular to road segment 1214 which is located abovethe tip of radial 1206. Radial 1204 runs in a southerly direction and isparallel to road portion 1216. In flat terrain, a mobile unit located atthe arrowhead of 1204 will have a clear line of sight to the basestation, while a mobile at arrow head 1206, will likely be obstructed bythe clutter along the radial such as buildings and trees. If standardmap pixel resolution processing is used for propagation losscalculations, inaccurate results may be obtained.

Use of Vector Features

The present invention avoids the accuracy limitations encountered innetwork planning using pixel level resolution by using vector featuresand modifying calculations accordingly. When the propagation path lossto a vector feature is calculated, the raster propagation path lossmodel is refined to accommodate the greater accuracy of the vectors.This enables other parameters such as incremental (intra-pixel)elevation, incremental (intra-pixel) coordinates for features, and fineroad resolution to be used when making propagation loss calculations.For example, the incremental elevation of a feature is added to theterrain elevation to provide a new mobile antenna height, thecoordinates and resolution of the feature are also used to calculate thepropagation path loss to the feature and to modify the land use averagedistribution to account for the placement of the vector. Using theseadditional parameters results in a more accurate solution.

FIGS. 13A and B illustrate the change in accuracy obtained using vectordata and the disclosed method. In FIG. 13A, a base station signal 1306is incident upon a mobile antenna 1302. The mobile antenna 1302 islocated on road 1304 within map pixel 1338 where the land use averagewindow (processing window) 1340 uses 5 map pixels 1330, 1332, 1334, 1336and 1338. If vector features are not employed in the calculation, thenfor situations where the road is not parallel to the radial, map pixel1338 is recognized as road, and the improved attenuation of a road isfactored into the land use average distribution as a complete pixel1342. Since roads are normally much narrower than a map pixel, errorsare introduced.

When the disclosed method is employed, as shown in FIG. 13B, the mobileantenna 1302 is placed in the center of the road 1304 at an elevationequal to the terrain elevation plus the vector elevation increment.Next, the weighted road attenuation factor is only applied to the halfof the road width 1314 that is facing the base station. In order tomaintain a processing window 1340 of 5 map pixels in length, theremaining map pixel width 1316 is averaged in as the low weight higherattenuation partial pixel.

FIG. 14 illustrates a road 1401 that is essentially perpendicular toradials 1402–1406 emanating from a base station 1420. After 1406, theroad 1401 bends until it is essentially parallel to a radial extendingto points 1412 through 1414. Computing the propagation path loss forperpendicular road points on radials 1402–1406 will be done as describedabove. In contrast, the propagation path loss for point 1414 uses theroad attenuation factor for all the pixels along the vector andtherefore shows significantly less signal attenuation at point 1414 thanat point 1406. If the loss at a point between 1412 and 1414 is required,say point 1416, it can be determined by interpolating between points1412 and 1414. For vectors, determining whether a vector is parallel toa radial is accomplished by comparing the angle of the vector to theangle of the radial. After the propagation path loss is calculated, thereceived power can be calculated using Eq. 1, shown previously.

Although the preferred embodiments of the invention have beenillustrated and described in detail, it will be readily apparent tothose skilled in the art that various modifications may be made thereinwithout departing from the spirit of the invention or from the scope ofthe appended claims. For example, propagation loss parameters can beincorporated to better account for weather conditions, the size andshape of structures, vehicle density, etc. In addition, the system andmethod can be used to deal with aircraft on flight paths rather thanvehicles on roads.

1. A method for simultaneously handling data planes for processing vector features in a wireless network planning system comprising: accepting a vector data plane and a raster data plane; utilizing a coordinate system stored as a coordinate system data plane; processing the vector data plane and the raster data plane using the coordinate system data plane to compute a distance to the vector feature that is within the boundaries of a pixel containing the vector feature; wherein the processing includes calculating a propagation loss for a wireless communications signal, and wherein the calculating comprises the steps of: determining a length of a radial from a base station to a mobile antenna; computing the propagation loss from said base station to an inner edge of a map pixel containing said mobile antenna; and determining a propagation loss from the inner edge of said map pixel containing said mobile antenna to a mobile antenna location using vector processing and a weighting function; and transferring the result to an output.
 2. The method of claim 1, wherein the raster data plane includes at least one raster variable.
 3. The method of claim 1, wherein the vector data plane includes at least one vector variable.
 4. The method of claim 1, wherein the coordinate system data plane is comprised of a geographical coordinate system.
 5. The method of claim 1, wherein the result is comprised of at least one data plane.
 6. The method of claim 1, wherein the vector data plane and the raster data plane is accepted over a network.
 7. The method of claim 1, wherein the output means is a network.
 8. A method for simultaneously handling data planes for processing vector features in a wireless network planning system comprising: accepting a vector data plane and a raster data plane; utilizing a coordinate system stored as a coordinate system data plane; processing the vector data plane and the raster data plane using the coordinate system data plane to compute a distance to the vector feature that is within the boundaries of a pixel containing the vector feature; wherein the processing includes redistributing traffic within a sector onto vectors located within said sector and wherein said redistributing comprises: calculating the total traffic within said sector; determining a scaling factor; using said scaling factor to spread said traffic over at least one vector point within said sector; and spreading the remaining traffic over the pixels within the sector; and transferring the result to an output.
 9. The method of claim 8, wherein the raster data plane includes at least one raster variable.
 10. The method of claim 8, wherein the vector data plane includes at least one vector variable.
 11. The method of claim 8, wherein the coordinate system data plane is comprised of a geographical coordinate system.
 12. The method of claim 8, wherein the result is comprised of at least one data plane.
 13. The method of claim 8, wherein the vector data plane and the raster data plane is accepted over a network.
 14. The method of claim 8, wherein the output means is a network. 